[hackermatic]

I hope commenters will dig into the author's citations' data, in line with HN's discussion guidelines, instead of just expressing a negative opinion about the thrust of the article. The quantifiable impact of genAI on code productivity is an important research question, and very much an open question subject to bias from all the players in the space -- especially once you factor in quality, maintainability, and bugs or revisions over time.

The GitClear whitepaper that Marcus cites tries to account for some of these factors, but they're biased by selling their own code quality tools. Likewise, GitHub's whitepapers (and subsequent marketing) tend to study the perception of productivity and quality by developers, and other fuzzy factors like the suggestion acceptance rate -- but not bug rate or the durability of accepted suggestions over time. (I think perceived productivity and enjoyment of one's job are also important values, but they're not what these products are being sold on.)